ph3Join Vonage and help us innovate cloud communications for businesses worldwide! Senior Data Scientist — Verify V2 Data Products, Insights Monetization /h3h3Mission /h3pBuild the quantitative foundation that proves and amplifies Verify v2's value—transforming verification telemetry into a reliable, customer-facing data infrastructure that demonstrates measurable ROI, optimizes channel economics, and lays the groundwork for an autonomous identity and verification platform. /ppYou'll own the end-to-end data pipeline from raw events to customer-visible metrics that answer the question every customer asks: "What is this product actually worth to my business?" /ph3What You'll Own /h3h31. Customer Value Infrastructure (Prove ROI at Every Level) /h3pbBuild the metrics that quantify customer-specific business impact: /b /pulliDesign and maintain a real-time bCustomer ROI Engine /b calculating cost-per-successful-verification, fraud savings, conversion lift, and time-to-value by customer, segment, and use case /liliCreate customer-facing bValue Dashboards /b showing verification success rates vs. industry benchmarks, cost efficiency trends, and projected savings /liliDevelop battribution models /b connecting verification outcomes to downstream business metrics (account activations, transaction completion, fraud prevented) /li /ulpbEstablish pricing intelligence at the customer level: /b /pulliBuild granular unit economics visibility: cost-to-serve, margin contribution, and channel mix efficiency per customer /liliModel willingness-to-pay signals and usage patterns to inform tiered pricing and custom packaging /liliQuantify the revenue impact of workflow configurations (Silent Auth-first vs. SMS fallback economics) /li /ulh32. Channel Performance Optimization (Make Every Verification Smarter) /h3pbCreate a single source of truth for channel economics: /b /pulliUnified performance metrics across SMS, Voice, Email, WhatsApp, and Silent Authentication: deliverability, latency, conversion rate, cost-per-success, and failure taxonomy /liliCountry × carrier × channel performance matrices with confidence intervals and anomaly flags /liliReal-time channel health monitoring with automated alerting for degradation /li /ulpbBuild the intelligence layer for workflow optimization: /b /pulliPredictive models for optimal channel routing (next-best-channel given geography, time, customer segment, historical performance) /liliFallback effectiveness analysis: quantify conversion recovery and cost trade-offs for each fallback path /liliSilent Authentication signal analysis: success/rejection drivers, speed benchmarks, and UX impact measurement /li /ulh33. Product Data Platform (Foundation for Autonomy) /h3pbDesign data architecture that enables autonomous decision-making: /b /pulliDefine the canonical event schema and taxonomy for all verification touchpoints (API calls, webhook events, workflow steps, outcomes) /liliBuild certified, versioned datasets powering self-serve analytics, ML models, and customer-facing products /liliImplement data quality infrastructure: lineage tracking, anomaly detection, freshness SLAs, and automated reconciliation /li /ulpbShip ML/analytics products that move toward autonomous verification: /b /pullibConversion propensity models /b:



predict verification success probability in real‑time to optimize routing /lilibFraud abuse detection /b: anomaly scoring for traffic pumping, IRSF patterns, and bot behavior—with automated response recommendations /lilibTime-to-verify prediction /b: forecast completion time to enable SLA commitments and dynamic timeout tuning /lilibCustomer segmentation /b: behavioral and commercial clustering for personalized workflows and pricing /li /ulh34. Monetization (Turn Data into Revenue) /h3pbDevelop data products that customers will pay for: /b /pullibVerification Intelligence Suite /b: premium analytics, industry benchmarks, and deliverability diagnostics /lilibWorkflow Optimizer /b: ML‑driven recommendations for channel sequencing, timeout configuration, and fallback strategies by geography and vertical /lilibFraud Protection Package /b: risk scoring, pumping detection, and abuse pattern alerts with quantified savings /li /ulpbDefine commercial success: /b /pulliPackage entitlements, usage thresholds, and upgrade triggers /liliTrack attach rates, retention lift, and expansion revenue attributable to data products /liliBuild the business case for each offering with clear ROI narratives /li /ulh3Key Responsibilities /h3ullibOwn the customer value narrative /b: Build and maintain the infrastructure that lets every customer (and our sales team) articulate Verify's ROI in dollars and percentages /lilibShip production ML systems /b: From feature engineering through deployment, monitoring, and iteration /lilibCreate reliable, self‑serve data products /b: Dashboards, APIs, and datasets that scale without manual intervention /lilibDrive pricing and packaging decisions /b: Provide the quantitative foundation for how we charge and what we bundle /lilibPartner across the organization /b: Work with Product, Engineering, Finance, Sales, and Customer Success to embed data into every decision /lilibReport to leadership /b: Own KPI narratives on margin drivers, growth levers, and competitive positioning /li /ulh3Success Measures /h3h3Area /h3h3Target KPIs /h3h3Customer Value Proof /h3p100% of enterprise customers have ROI dashboards; X% increase in documented customer savings /ph3Channel Optimization /h3p+X% conversion rate improvement; −X seconds median time-to-verify; −X% cost-per-success /ph3Fraud Abuse /h3p−X% fraudulent traffic; $Xm in prevented losses; x% false positive rate /ph3Data Product Revenue /h3pX% attach rate on premium insights; $Xm incremental ARR from data products /ph3Platform Readiness /h3pCertified datasets powering ≥3 autonomous routing decisions; xms model inference latency /ph3What "Great" Looks Like /h3h3Core Data Science /h3ulliExperimentation design and causal inference (A/B testing, CUPED, uplift modeling, instrumental variables) /liliPredictive modeling: classification, survival analysis, time series,



real‑time scoring /liliAnomaly detection with adversarial thinking (fraud patterns, traffic manipulation, abuse signals) /liliCustomer analytics: segmentation, LTV modeling, churn prediction, cohort economics /li /ulh3Data Engineering Fluency /h3ulliStrong SQL; Python (pandas, scikit-learn, PySpark); comfortable shipping production code /liliEvent‑driven architecture: streaming pipelines and real‑time analysis and adaptation (Apache Flink), webhook processing, idempotency, late‑arrival handling /liliData modeling: star schemas, semantic layers, data contracts, metric certification /liliMLOps: feature stores, model monitoring, CI/CD for analytics, orchestration (Airflow/Dagster) /li /ulh3Product Commercial Analytics /h3ulliPricing analytics: unit economics, willingness-to-pay estimation, margin optimization /liliFunnel analysis for multi‑step, multi‑channel workflows /liliDashboard design and narrative clarity (Looker, Tableau, dbt metrics layer) /liliPackaging and monetization strategy for data products /li /ulh3Domain Expertise (Highly Valued) /h3ulliCPaaS, verification, or 2FA: OTP mechanics, deliverability constraints, carrier relationships /liliSilent Authentication: network‑based verification, success/rejection drivers, integration patterns /liliFraud and risk: traffic pumping, IRSF, bot detection, abuse economics /liliPrivacy and compliance: GDPR/CCPA, data minimization, audit requirements, customer‑facing data controls /li /ulh3Background /h3ulli5–8+ years in data science/analytics, with ≥2 years building and shipping data products /liliTrack record of translating ambiguous business questions into measurable outcomes /liliExperience in B2B SaaS, identity/auth, fintech, messaging/telecom, or fraud analytics preferred /liliDemonstrated ability to influence product and pricing decisions with data /li /ulh3Why This Role Matters /h3pVerification is shifting from a cost center to a strategic differentiator. The data infrastructure you build will: /pullibProve value /b — Give every customer undeniable evidence of ROI /lilibOptimize economics /b — Make every verification faster, cheaper, and more reliable /lilibEnable autonomy /b — Lay the foundation for a platform that routes, optimizes, and protects without human intervention /li /ulpYou don't need all the preferred qualifications to make a valuable impact on our team. Our employees and customers come from diverse backgrounds, so if you're passionate about what you could achieve at Vonage, we'd love to hear from you. /ppTo learn how we process your personal data during the recruitment process, please refer to our bPrivacy Notice /b . /ph3Who we are: /h3pVonage is a integral cloud communications leader. And your talent will further help brands - such as Airbnb, Viber, WhatsApp, and Snapchat - accelerate their digital transformation through our fully programmable-based unified communications, contact center solutions, and communications APIs. Ready to innovate? Then join us today. /ppNote: The purpose of this profile is to provide a general summary of essential responsibilities for the position and is not meant as an exhaustive list. Assignments may differ for individuals within the same role based on business conditions, departmental need or geographic location. /p /p #J-18808-Ljbffr

📌 Senior Data Scientist (Barcelona)
🏢 Vonage
📍 Barcelona